State Variables Estimation for Control of Elastic Crane Using Vision Sensor Data

The estimation of state variables plays a significant role in the control of ship-mounted cranes. Elastic-ship mounted crane can have very complex dynamic vibrations during their operations. A vision sensor (i.e. camera) realizing a contactless measurement sensor can be used to measure the deformations. A dynamic model of elastic-ship mounted crane based on finite element technique is used in this work. Two observers are designed, the first one to estimate the state variables using camera measurement, the second one using conventional measurement of mechanical variables. The effects of time delay and noise in states estimation are shown by the comparison of the states from the different measured input data. The main goal of the work is to develop an approach to combine suitable measurement devices easy to realize with improved reliability. The controller uses the estimated states and the roll angle to generate the required control input to damp the system vibrations. Experimental results show that the observers can estimate the states and the unknown disturbance acting on the payload very well and the controller can reduce effectively the payload pendulations.